{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 问题描述\n",
    "以作业给出的代码为基础，实现卷积的前向传播代码。\n",
    "\n",
    "给出代码的运行log截图并提供心得体会文档解释计算过程。\n",
    "\n",
    "- 没有明显报错的正常的log输出 60分。\n",
    "- 代码中有几个循环，每个循环的作用，里面做了什么样的操作 40分（根据是否能够准确流畅的描述酌情扣分）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这个作业里，需要手写一个跟tensorflow里面的conv2d类似的卷积函数。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了保证更好的服务质量，请留下作业完成者的基本信息。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:48:29.188462Z",
     "start_time": "2018-05-30T09:48:28.155066Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "C:\\Users\\ilove\\Anaconda3\\envs\\tfl1.14\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.14.0\n"
     ]
    }
   ],
   "source": [
    "# 声明一些用到的库\n",
    "import base64\n",
    "from io import BytesIO\n",
    "\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from matplotlib import pyplot as plt\n",
    "from PIL import Image\n",
    "\n",
    "%matplotlib inline\n",
    "print(tf.__version__)\n",
    "# assert tf.__version__ >= '1.4.0', 'Please upgrade your tensorflow installation to v1.4.* or later!'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "读入图片，因为没想到怎么把文件跟ipynb放到一起，所以这里只能将图片base64化为一个字符串直接放到这里。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:48:31.310610Z",
     "start_time": "2018-05-30T09:48:30.801007Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(350, 500, 3)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_b = 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'\n",
    "inf = BytesIO(base64.b64decode(img_b))\n",
    "img = Image.open(inf)\n",
    "img = np.asarray(img, dtype=np.uint8)\n",
    "plt.imshow(img)\n",
    "print(img.shape)\n",
    "\n",
    "# only R is used for test\n",
    "# img = img[:, :, 0]\n",
    "# print(img.shape)\n",
    "# print(img)\n",
    "\n",
    "#img = img[0:3, 0:3]\n",
    "#print(img.shape)\n",
    "#print(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "查看一下图像的均值，这里图像像素值在0-255之间，神经网络里面，数据的值需要做一下归一化处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:48:33.841063Z",
     "start_time": "2018-05-30T09:48:33.793587Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "171.61454476190477\n",
      "0.6729982147525674\n",
      "(1, 350, 500, 3)\n",
      "[[[[0.69803922 0.65882353 0.65490196]\n",
      "   [0.70980392 0.67058824 0.66666667]\n",
      "   [0.69803922 0.65882353 0.65490196]\n",
      "   ...\n",
      "   [0.59215686 0.58431373 0.53333333]\n",
      "   [0.6        0.59215686 0.54117647]\n",
      "   [0.6        0.59215686 0.54117647]]\n",
      "\n",
      "  [[0.69803922 0.65882353 0.65490196]\n",
      "   [0.71372549 0.6745098  0.67058824]\n",
      "   [0.70196078 0.6627451  0.65882353]\n",
      "   ...\n",
      "   [0.58431373 0.57647059 0.5254902 ]\n",
      "   [0.60392157 0.59607843 0.54509804]\n",
      "   [0.60784314 0.6        0.54901961]]\n",
      "\n",
      "  [[0.70196078 0.6627451  0.65882353]\n",
      "   [0.71372549 0.6745098  0.67058824]\n",
      "   [0.70588235 0.66666667 0.6627451 ]\n",
      "   ...\n",
      "   [0.6        0.58431373 0.54117647]\n",
      "   [0.60784314 0.59215686 0.54901961]\n",
      "   [0.6        0.58431373 0.54117647]]\n",
      "\n",
      "  ...\n",
      "\n",
      "  [[0.76862745 0.75294118 0.74901961]\n",
      "   [0.78823529 0.77254902 0.76862745]\n",
      "   [0.78823529 0.77254902 0.76862745]\n",
      "   ...\n",
      "   [0.76470588 0.77254902 0.76078431]\n",
      "   [0.75686275 0.76470588 0.75294118]\n",
      "   [0.76862745 0.77647059 0.76470588]]\n",
      "\n",
      "  [[0.83921569 0.82352941 0.81960784]\n",
      "   [0.83921569 0.82352941 0.81960784]\n",
      "   [0.82745098 0.81176471 0.80784314]\n",
      "   ...\n",
      "   [0.76470588 0.77254902 0.76078431]\n",
      "   [0.75686275 0.76470588 0.75294118]\n",
      "   [0.77647059 0.78431373 0.77254902]]\n",
      "\n",
      "  [[0.80784314 0.79215686 0.78823529]\n",
      "   [0.80392157 0.78823529 0.78431373]\n",
      "   [0.80392157 0.78823529 0.78431373]\n",
      "   ...\n",
      "   [0.76862745 0.77647059 0.76470588]\n",
      "   [0.76862745 0.77647059 0.76470588]\n",
      "   [0.77254902 0.78039216 0.76862745]]]]\n"
     ]
    }
   ],
   "source": [
    "print(img.mean())\n",
    "img = img/255\n",
    "print(img.mean())\n",
    "\n",
    "img = np.expand_dims(img, axis=0) # 将图像处理成为一个batch\n",
    "# img = np.expand_dims(img, axis=3) # 将图像处理成为一个batch\n",
    "print(img.shape)\n",
    "print(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "实现一下卷积函数，这里 filter 为输入的卷积核的权重，其 shape 为 **height x width x in_channels x out_channels**，也就是说，这里卷积核的个数是通过最后的 **out_channels** 反映出来的。stride 我们定义一个标量，同时用于宽高。padding 仿照 tf，只取 same 和 valid 两个值，函数内部需要自动计算需要的 padding。为了与 tf 的接口保持一致，数据输入也是四维的，第一维是 batchsize，这里只有一张图片，所以是 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[[0.91404336 0.7429845  0.33059612 0.34056571 0.14182774 0.03013188\n",
      "    0.81503543 0.43532827]\n",
      "   [0.13544533 0.86692497 0.11464373 0.79966489 0.96977154 0.17548236\n",
      "    0.84062526 0.97038237]\n",
      "   [0.56294844 0.26683077 0.62604725 0.59192422 0.51941596 0.71134379\n",
      "    0.62181635 0.8755119 ]]\n",
      "\n",
      "  [[0.19743933 0.87842928 0.30036013 0.02219805 0.87652048 0.36674748\n",
      "    0.49860777 0.90713766]\n",
      "   [0.41859877 0.63605346 0.51069208 0.63963405 0.81401189 0.75319573\n",
      "    0.49997575 0.71196349]\n",
      "   [0.77317441 0.07594509 0.1475857  0.69649741 0.05127772 0.16841962\n",
      "    0.48540441 0.78462907]]\n",
      "\n",
      "  [[0.446001   0.58580933 0.59247528 0.8838602  0.35794886 0.46898513\n",
      "    0.63347074 0.52516406]\n",
      "   [0.50371077 0.71018104 0.29266891 0.8741159  0.55415634 0.88042335\n",
      "    0.07208161 0.13816575]\n",
      "   [0.47932013 0.43958513 0.86697841 0.03726248 0.52339266 0.96213535\n",
      "    0.81889275 0.41220125]]\n",
      "\n",
      "  [[0.41593662 0.23914241 0.92822652 0.34709814 0.82990427 0.64554311\n",
      "    0.87271159 0.13977658]\n",
      "   [0.86275397 0.66091745 0.96234116 0.58602654 0.79034313 0.44887009\n",
      "    0.33600388 0.04463482]\n",
      "   [0.11107813 0.11508682 0.1684806  0.94852664 0.67255638 0.89806123\n",
      "    0.09178821 0.12932406]]\n",
      "\n",
      "  [[0.78593788 0.34990565 0.31915355 0.35120079 0.14384073 0.9754528\n",
      "    0.38218656 0.96609754]\n",
      "   [0.15133343 0.87425588 0.41746403 0.84841802 0.11754038 0.7682465\n",
      "    0.18433617 0.63690383]\n",
      "   [0.09074204 0.48157711 0.86911897 0.90672832 0.51751191 0.28049804\n",
      "    0.18522218 0.72571098]]]\n",
      "\n",
      "\n",
      " [[[0.18617733 0.93657736 0.80278647 0.00422835 0.48218962 0.76181046\n",
      "    0.92285035 0.77253467]\n",
      "   [0.29371212 0.67807821 0.09729437 0.13234185 0.22998033 0.73273206\n",
      "    0.26247902 0.21046481]\n",
      "   [0.62630226 0.32706929 0.12086909 0.83350137 0.37087491 0.93265591\n",
      "    0.67101542 0.81210275]]\n",
      "\n",
      "  [[0.34494102 0.02073409 0.38639145 0.75976982 0.81261099 0.89450553\n",
      "    0.92863432 0.64144474]\n",
      "   [0.27169746 0.47317555 0.82137305 0.38414389 0.62512619 0.54228702\n",
      "    0.02886985 0.91387555]\n",
      "   [0.33655389 0.22391291 0.07992104 0.3947723  0.61262924 0.26451008\n",
      "    0.29431173 0.83869641]]\n",
      "\n",
      "  [[0.96664232 0.23334488 0.75703334 0.23026439 0.00803501 0.24347641\n",
      "    0.29947998 0.71247407]\n",
      "   [0.36467492 0.95100078 0.94020069 0.79354593 0.18850153 0.42723448\n",
      "    0.86593198 0.5140679 ]\n",
      "   [0.42961441 0.79077971 0.73094652 0.89439608 0.35125586 0.32971754\n",
      "    0.22576737 0.65135911]]\n",
      "\n",
      "  [[0.2091123  0.55646064 0.45462465 0.86775002 0.56264683 0.09834163\n",
      "    0.03273089 0.37044726]\n",
      "   [0.99220894 0.0595825  0.40377753 0.75066274 0.15108934 0.03776231\n",
      "    0.80872116 0.43337399]\n",
      "   [0.63581356 0.64179324 0.24610525 0.08099621 0.1749375  0.43491623\n",
      "    0.41983945 0.57572132]]\n",
      "\n",
      "  [[0.26994799 0.47811351 0.96439413 0.62752041 0.37739633 0.66192481\n",
      "    0.3999533  0.68307037]\n",
      "   [0.17995237 0.02922348 0.37767315 0.01742026 0.88497503 0.99710173\n",
      "    0.57490527 0.9274955 ]\n",
      "   [0.60945668 0.50225777 0.02855781 0.66765199 0.87640256 0.26009132\n",
      "    0.84112459 0.58305831]]]\n",
      "\n",
      "\n",
      " [[[0.33629805 0.18218242 0.27712712 0.96564412 0.04671716 0.44771574\n",
      "    0.69744687 0.94668739]\n",
      "   [0.28701209 0.52347798 0.86077939 0.3430314  0.06875549 0.84323257\n",
      "    0.35256549 0.03726074]\n",
      "   [0.23996875 0.020951   0.38645506 0.58407954 0.12328164 0.65424513\n",
      "    0.25771673 0.5357024 ]]\n",
      "\n",
      "  [[0.08598089 0.6335393  0.91195593 0.234457   0.6423849  0.05080467\n",
      "    0.40299228 0.64056072]\n",
      "   [0.54126976 0.65241607 0.69390291 0.71419631 0.8217777  0.93821037\n",
      "    0.41349048 0.35926252]\n",
      "   [0.21045235 0.42800202 0.12762702 0.28648659 0.90309283 0.8702039\n",
      "    0.12593308 0.36128281]]\n",
      "\n",
      "  [[0.60828927 0.27184923 0.07963419 0.17950953 0.54766301 0.57356046\n",
      "    0.08098471 0.14492796]\n",
      "   [0.34068624 0.43229277 0.12127392 0.69908232 0.54916599 0.36683663\n",
      "    0.74689765 0.05989977]\n",
      "   [0.72677088 0.71735898 0.86982195 0.95639833 0.68214105 0.35100902\n",
      "    0.1830638  0.57368206]]\n",
      "\n",
      "  [[0.47978013 0.28660914 0.99210399 0.18306184 0.58837072 0.57175547\n",
      "    0.36702534 0.17387543]\n",
      "   [0.20724341 0.10826534 0.54301721 0.76115445 0.62876656 0.43694248\n",
      "    0.10374998 0.91076184]\n",
      "   [0.11462133 0.67016154 0.32474461 0.95500346 0.46859748 0.39685445\n",
      "    0.00875591 0.73183021]]\n",
      "\n",
      "  [[0.5405559  0.14039845 0.31428919 0.50025711 0.92461631 0.89706104\n",
      "    0.45432133 0.72173215]\n",
      "   [0.28866465 0.14908514 0.54660215 0.15676813 0.22482285 0.21981393\n",
      "    0.02087247 0.88390296]\n",
      "   [0.54556628 0.94610576 0.11605517 0.41631804 0.6976262  0.65191648\n",
      "    0.26460767 0.77602986]]]\n",
      "\n",
      "\n",
      " [[[0.42796431 0.692291   0.85996472 0.33762715 0.38994891 0.00651802\n",
      "    0.72575538 0.56196177]\n",
      "   [0.4902411  0.40101721 0.4872616  0.59273771 0.70772441 0.7058761\n",
      "    0.91673781 0.15149293]\n",
      "   [0.8341588  0.75597532 0.99803341 0.56209834 0.47705114 0.79231637\n",
      "    0.635424   0.18810031]]\n",
      "\n",
      "  [[0.95306278 0.09515797 0.10184494 0.66778401 0.81686682 0.11098631\n",
      "    0.47983237 0.41930829]\n",
      "   [0.8846519  0.4735788  0.82711953 0.80354494 0.23714916 0.75211829\n",
      "    0.87482794 0.2968947 ]\n",
      "   [0.93037128 0.75670817 0.43018594 0.69777387 0.82824082 0.21278654\n",
      "    0.8247223  0.37292338]]\n",
      "\n",
      "  [[0.26315763 0.05221416 0.75419708 0.09521751 0.05376671 0.08375244\n",
      "    0.42980862 0.34269813]\n",
      "   [0.90244258 0.55563184 0.26843685 0.95923779 0.24735479 0.81178901\n",
      "    0.84352634 0.68320789]\n",
      "   [0.76005552 0.80403529 0.76260885 0.80702613 0.50150537 0.37987919\n",
      "    0.658999   0.09808081]]\n",
      "\n",
      "  [[0.75403111 0.94920231 0.88563235 0.77493647 0.99170335 0.46035091\n",
      "    0.81135523 0.3892767 ]\n",
      "   [0.99750302 0.90895913 0.01559753 0.96219794 0.33447113 0.44352099\n",
      "    0.92526139 0.57055168]\n",
      "   [0.98901241 0.70832396 0.86878134 0.49772032 0.16665971 0.86588449\n",
      "    0.79451407 0.10364018]]\n",
      "\n",
      "  [[0.97026932 0.4941092  0.47726608 0.71655292 0.93489394 0.04633271\n",
      "    0.28077053 0.60907593]\n",
      "   [0.64781666 0.90873898 0.28305786 0.61749407 0.68755759 0.67601294\n",
      "    0.13134207 0.89318336]\n",
      "   [0.36768236 0.54237864 0.34139094 0.40174606 0.51494495 0.93910574\n",
      "    0.01204626 0.15939015]]]\n",
      "\n",
      "\n",
      " [[[0.36515188 0.33655316 0.2948769  0.30162672 0.189103   0.74479704\n",
      "    0.15088937 0.43193094]\n",
      "   [0.00572477 0.82305389 0.13272952 0.65810013 0.77603757 0.23785808\n",
      "    0.25566849 0.62662596]\n",
      "   [0.17252593 0.30792831 0.76668295 0.14791462 0.59325115 0.4731513\n",
      "    0.9667777  0.00235407]]\n",
      "\n",
      "  [[0.24663324 0.55289145 0.89794211 0.89967659 0.11093708 0.67795719\n",
      "    0.95342471 0.21370862]\n",
      "   [0.77318489 0.10425936 0.31177086 0.5332665  0.07449605 0.87778759\n",
      "    0.37470545 0.37015979]\n",
      "   [0.62817084 0.1414984  0.74416772 0.9135075  0.86914145 0.42532787\n",
      "    0.45213951 0.60999417]]\n",
      "\n",
      "  [[0.68890875 0.40740638 0.20479002 0.54363747 0.0651965  0.91139643\n",
      "    0.9174192  0.87007895]\n",
      "   [0.10598829 0.47335512 0.48184613 0.30159996 0.41050142 0.20108738\n",
      "    0.9985143  0.38789409]\n",
      "   [0.34288457 0.84275476 0.43297091 0.78524474 0.06475209 0.50705725\n",
      "    0.50615847 0.37787443]]\n",
      "\n",
      "  [[0.55252103 0.16054677 0.240844   0.55004585 0.95426173 0.41286646\n",
      "    0.55661566 0.23087101]\n",
      "   [0.7278864  0.66602348 0.00177963 0.61554653 0.7355538  0.72096992\n",
      "    0.25089743 0.14772973]\n",
      "   [0.89523357 0.01347618 0.52644793 0.29115898 0.13321493 0.49481622\n",
      "    0.04568096 0.04665346]]\n",
      "\n",
      "  [[0.71567429 0.81838691 0.1128594  0.35304051 0.87814072 0.09022001\n",
      "    0.14098722 0.4100666 ]\n",
      "   [0.18316665 0.93673276 0.50584573 0.91963564 0.26487332 0.87778568\n",
      "    0.00264166 0.01100969]\n",
      "   [0.9036188  0.38924527 0.65362751 0.12384861 0.82224126 0.58905563\n",
      "    0.54117458 0.25232698]]]]\n"
     ]
    }
   ],
   "source": [
    "filter = np.random.uniform(size=[5, 5, 3, 8])\n",
    "#filter = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9]).reshape((3,3,1,1))\n",
    "#filter = np.ones([3, 3, 1, 1])\n",
    "print(filter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:49:25.813788Z",
     "start_time": "2018-05-30T09:49:25.765422Z"
    }
   },
   "outputs": [],
   "source": [
    "def conv2d(input, filter, stride, padding):\n",
    "    # batchsize x height x width x in_channels\n",
    "    in_s = input.shape\n",
    "    # height x width x in_channels x out_channels\n",
    "    f_s = filter.shape \n",
    "\n",
    "    assert len(in_s) == 4, 'input size rank 4 required!'\n",
    "    assert len(f_s) == 4, 'filter size rank 4 required!'\n",
    "    assert f_s[2] == in_s[3], 'intput channels not match filter channels.'\n",
    "    assert f_s[0] >= stride and f_s[1] >= stride, 'filter should not be less than stride!'\n",
    "    assert padding in [\n",
    "        'SAME', 'VALID'], 'padding value[{0}] not allowded!!'.format(padding)\n",
    "\n",
    "    (batchsize, in_height, in_width, in_channels) = in_s[:4] \n",
    "    (filter_height, filter_width, _, out_channels) = f_s[:4] \n",
    "    strides_height = strides_width = stride\n",
    "    \n",
    "    if padding == 'VALID':\n",
    "        out_width = int(np.ceil((in_width - filter_width + 1) / strides_width)) # (结果问上取整)\n",
    "        out_height = int(np.ceil((in_height - filter_height + 1) / strides_height)) # (结果向上取整)     \n",
    "        #print(in_s, f_s, out_height, out_width)\n",
    "        output = np.zeros((batchsize, out_height, out_width, out_channels), np.float64)\n",
    "        #print(output.shape)\n",
    "        for b in range(batchsize):  \n",
    "            for h in range(out_height):\n",
    "                for w in range(out_width):\n",
    "                    for i in range(out_channels):\n",
    "                        output[b, h, w, i] = np.sum(input[b, h*stride: h*stride + filter_height, w*stride : w*stride + filter_width, 0:in_channels] * filter[0: filter_height, 0: filter_width, 0:in_channels, i])\n",
    "                        # print(\"output({}, {}, {}, {})={}\".format(b, h, w, i, output[b, h, w, i]))\n",
    "        return output\n",
    "                   \n",
    "    if padding == 'SAME':\n",
    "        # 提示： 关于SAME和VALID的区别，请参考：https://www.tensorflow.org/api_docs/python/tf/nn/convolution\n",
    "        out_height = int(np.ceil(in_height / strides_height)) # (结果向上取整)\n",
    "        out_width = int(np.ceil(in_width / strides_width)) # (结果向上取整)\n",
    "        \n",
    "        pad_height = max( (out_height - 1) * strides_height + filter_height - in_height, 0)\n",
    "        pad_width = max((out_width - 1) * strides_width + filter_width - in_width, 0)\n",
    "        pad_top = int(pad_height / 2) #（结果向下取整）\n",
    "        pad_bottom = pad_height - pad_top\n",
    "        pad_left = int(pad_width / 2) #（结果向下取整）\n",
    "        pad_right = pad_width - pad_left\n",
    "        \n",
    "        #print(in_s, f_s, out_height, out_width, pad_height, pad_width, pad_top, pad_bottom, pad_left, pad_right)\n",
    "        output = np.zeros((batchsize, out_height, out_width, out_channels), np.float64)\n",
    "        #print(output.shape)        \n",
    "        \n",
    "        pad_input = np.zeros((batchsize, pad_height + in_height, pad_width + in_width, in_channels), np.float64)\n",
    "        #print(\"pad_input.shape = {}\".format(pad_input.shape))  \n",
    "        \n",
    "        pad_input[:batchsize, pad_top: pad_top + in_height, pad_left: pad_left + in_width, 0: in_channels] = input[:batchsize, :, :, 0: in_channels]       \n",
    "        for b in range(batchsize):  \n",
    "            for h in range(out_height):\n",
    "                for w in range(out_width):\n",
    "                    for i in range(out_channels):\n",
    "                        output[b, h, w, i] = np.sum(pad_input[b, h*stride: h*stride + filter_height, w*stride : w*stride + filter_width, 0: in_channels] * filter[0: filter_height, 0: filter_width, 0: in_channels, i])\n",
    "                        # print(\"output({}, {}, {}, {})={}\".format(b, h, w, i, output[b, h, w, i]))\n",
    "        return output    \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "怎么验证上面的卷积函数是正确的呢？用 tensorflow 里面已经实现好的卷积函数进行同样的计算，结果相同即可认为上面的实现是正确的。需要注意的是，因为浮点型有精度的问题，所以比较的时候需要检查参差。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:49:27.229074Z",
     "start_time": "2018-05-30T09:49:27.141426Z"
    }
   },
   "outputs": [],
   "source": [
    "# 先定义个计算图用于运行tf\n",
    "input_tensor = tf.placeholder(\n",
    "    tf.float32, shape=[None, None, None, None], name='input')\n",
    "filter_tensor = tf.placeholder(\n",
    "    tf.float32, shape=[None, None, None, None], name='filter')\n",
    "\n",
    "output_tensor1 = tf.nn.conv2d(\n",
    "    input_tensor, filter_tensor, padding='SAME', strides=[1, 2, 2, 1])\n",
    "\n",
    "output_tensor2 = tf.nn.conv2d(\n",
    "    input_tensor, filter_tensor, padding='VALID', strides=[1, 3, 3, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:49:38.333357Z",
     "start_time": "2018-05-30T09:49:38.280895Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test 1 passed... with difference = 2.6139902083650737e-06\n",
      "\n",
      "test 2 passed... with difference = 2.6632226649784114e-06 \n",
      "\n",
      "Your final score:[100]\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    final_score = 0  # 这个是最终得分\n",
    "\n",
    "    filter = np.random.uniform(size=[5, 5, 3, 8])\n",
    "\n",
    "    output = conv2d(img, filter, 2, 'SAME')\n",
    "\n",
    "    with tf.Session() as sess:\n",
    "        output_tf = sess.run(\n",
    "            output_tensor1,\n",
    "            feed_dict={\n",
    "                input_tensor: img,\n",
    "                filter_tensor: filter\n",
    "            })\n",
    "\n",
    "    assert output.shape == output_tf.shape, 'shape mismatch [{}] vs [{}]'.format(\n",
    "        output.shape, output_tf.shape)\n",
    "    final_score += 20  # shape算对了得20分\n",
    "\n",
    "    diff = np.mean(np.abs(output - output_tf))\n",
    "    assert diff < 1e-5, 'value mismatch [{}]'.format(\n",
    "        diff)  # 如果这一行没有报错的话，那么实现可以认为是正确的。\n",
    "    final_score += 30  # 数值算对了得30分\n",
    "\n",
    "    print('test 1 passed... with difference = {}\\n'.format(diff))\n",
    "\n",
    "    filter = np.random.uniform(size=[5, 5, 3, 8])\n",
    "\n",
    "    output = conv2d(img, filter, 3, 'VALID')\n",
    "    with tf.Session() as sess:\n",
    "        output_tf = sess.run(\n",
    "            output_tensor2,\n",
    "            feed_dict={\n",
    "                input_tensor: img,\n",
    "                filter_tensor: filter\n",
    "            })\n",
    "\n",
    "    assert output.shape == output_tf.shape, 'shape mismatch [{}] vs [{}]'.format(\n",
    "        output.shape, output_tf.shape)\n",
    "    final_score += 20  # shape算对了得20分\n",
    "\n",
    "    diff = np.mean(np.abs(output - output_tf))\n",
    "    assert diff < 1e-5, 'value mismatch [{}]'.format(\n",
    "        diff)  # 如果这一行没有报错的话，那么实现可以认为是正确的。\n",
    "    final_score += 30  # 数值算对了得30分\n",
    "\n",
    "    print('test 2 passed... with difference = {} \\n'.format(diff))\n",
    "except Exception as ex:\n",
    "    print(ex)\n",
    "\n",
    "print('Your final score:[{}]'.format(final_score))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来，用我们自己做的卷积函数，执行几步卷积"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-30T09:50:03.641983Z",
     "start_time": "2018-05-30T09:50:03.547648Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 175, 250, 8)\n",
      "(1, 88, 125, 16)\n",
      "(1, 29, 41, 24)\n"
     ]
    }
   ],
   "source": [
    "# input  1 x 350 x 500 x 3\n",
    "filter1 = np.random.uniform(size=[3, 3, 3, 8])\n",
    "padding1 = 'SAME'\n",
    "stride1 = 2\n",
    "output1 = conv2d(img, filter1, stride1, padding1)\n",
    "print(output1.shape)\n",
    "# output 1 x 175 x 250 x 8\n",
    "\n",
    "# input 1 x 175 x 250 x 8\n",
    "filter2 = np.random.uniform(size=[5, 5, 8, 16])\n",
    "padding2 = 'SAME'\n",
    "stride2 = 2\n",
    "output2 = conv2d(output1, filter2, stride2, padding2)\n",
    "print(output2.shape)\n",
    "# output 1 x 88 x 125 x 16\n",
    "\n",
    "# input 1 x 88 x 125 x 16\n",
    "filter2 = np.random.uniform(size=[3, 3, 16, 24])\n",
    "padding2 = 'VALID'\n",
    "stride2 = 3\n",
    "output2 = conv2d(output2, filter2, stride2, padding2)\n",
    "print(output2.shape)\n",
    "# output 1 x 29 x 41 x 24\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 思考一下，上面的 shape 数据是如何得出来的呢？\n",
    "\n",
    "1. 参考以下的资料: \n",
    "> https://cloud.tencent.com/developer/article/1501980  \n",
    "> https://github.com/Ty112358/conv2d/blob/master/conv2d.py  \n",
    "> https://github.com/vamsig7/SImple_image_Conv2d/blob/master/General_Method  \n",
    "> https://github.com/anavgagneja/conv2d/blob/master/conv.py  \n",
    "  \n",
    "2. 做如下定义：    \n",
    "> 输入 (input) 的尺寸中高和宽分别定义为 in_height、in_width。  \n",
    "> 卷积核 (kernel/filter) 的高和宽分别定义为 filter_height、filter_width。  \n",
    "> 输出 (output) 的尺寸中高和宽分别定义为 output_height、output_widh。  \n",
    "> 步长 (stride) 的高宽方向分别定义为 strides_height、 strides_width。(本题纵向与横向的步长是相等的，用 stride 表示)  \n",
    " \n",
    "3. ‘VALID’（实际上就是不做填充 - no padding）  \n",
    "输出宽和高的公式分别为:  \n",
    "> output_width = (in_width - filter_width + 1)/strides_width (结果向上取整)  \n",
    "> output_height = (in_height - filter_height + 1)/strides_height (结果向上取整)  \n",
    "   \n",
    "4. ‘SAME’（以 0 填充到滤波器可以到达输入(图像)边缘为止）   \n",
    "输出的宽和高与卷积核没有关系，具体公式如下:  \n",
    "> out_width = in_width / strides_width (结果向上取整)  \n",
    "> out_height = in_height / strides_height (结果向上取整)  \n",
    "  \n",
    "5.  补零的规则很重要，见如下公式:   \n",
    "> pad_height = max((out_height - 1) \\* strides_height + filter_height - in_height, 0)    \n",
    "> pad_width = max((out_width - 1) \\* strides_width + filter_width - in_width, 0)  \n",
    "> pad_top = pad_height / 2（结果向下取整）   \n",
    "> pad_bottom = pad_height - pad_ top  \n",
    "> pad_left = pad_width / 2（结果向下取整）  \n",
    "> pad_right = pad_width - pad_left  \n",
    "    \n",
    "6.  可以看到补零的规则是**优先在输入矩阵的右边和底边补零**，例如补零的行数为三行。则 top 一行，bottom 两行；如果补零的行数为一行，则补在 bottom。**因为filter是从左向右从上到下滑动的，所以滑动到右边或者底边的时候有可能会因为大步长而损失边界信息，所以优先在右边和底边补零**。   \n",
    "> pad_height 代表高度方向填充 0 的行数，pad_width 代表宽度方向填充 0 的列数，以此类推。 \n",
    "7.  卷积核的滤波器个数决定输出的个数。 \n",
    "8.  卷积核的滤波器通道数必须等于输入的通道数（卷积核的第三维参数必须等于输入的第四维参数）。\n",
    "9.  输入的高和宽决定输出的高和宽。\n",
    "10. 输出就是常说的 feature map。\n",
    "\n"
   ]
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    "#### 没有明显报错的正常的 log 输出 60分。\n",
    "\n",
    "1. 使用 tf.float32 时误差在 e-06 等级，使用 tf.float64 时误差降低到 e-15 等级，都小于题目要求的 e-05 。  \n",
    "2. 两次测试都能通过，得到 100 分。  "
   ]
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   "metadata": {},
   "source": [
    "#### 代码中有几个循环，每个循环的作用，里面做了什么样的操作 40分（根据是否能够准确流畅的描述酌情扣分）。\n",
    "\n",
    "1. 使用 4 个循环, 最外层循环 b 代表一次训练或测验使用的数据量（本题指的是输入的图像\"帧数\"，但本题只使用 1 帧图像，所以其实可以省去这个循环）, 第 2 层循环 h 代表卷积核（的某个滤波器）向下移动的过程，第 3 层循环 w 代表卷积核（的某个滤波器滤波器）向右移动的过程，最内层循环 i 代表使用卷积核的第 i 个滤波器进行卷积运算：  \n",
    "```\n",
    "    for b in range(batchsize):\n",
    "        for h in range(out_height):  \n",
    "            for w in range(out_width):  \n",
    "                for i in range(out_channels):  \n",
    "                    output[b, h, w, i] = np.sum(  \n",
    "                        pad_input[b, h*stride: h*stride + filter_height,   \n",
    "                                w*stride : w*stride + filter_width,   \n",
    "                                0: in_channels] *   \n",
    "                        filter[0: filter_height, 0: filter_width, 0: in_channels, i])  \n",
    "```\n",
    "2. 利用 Python 语言强大的 “:”  运算子进行卷积运算，一行便可以進行多維的捲積運算，不需要再拆分成更多层的循环进行不同维度上的卷积/加权及加总运算。\n",
    "3. 在‘SAME’模式下，需要先扩张输入数据的高与宽及大量复制数据，也是直接利用 Python 语言的 “:” 运算子，如果没使用底层硬件的平行并发机制，猜测实际运用的也是循环。"
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